The real estate industry has long been perceived as an "analog" industry. However, rapid advances in technology in recent years have dramatically changed this situation.
From 2020, when I founded INA & Associates, Inc. to the present, the wave of digital transformation in the real estate industry has steadily accelerated. In particular, the introduction of artificial intelligence (AI) technology has the potential to fundamentally change the traditional concept of real estate transactions.
As of 2024, the real estate tech market is estimated to be 940.2 billion yen, up 21.1% from the previous year, and is projected to reach 2.3 trillion yen by 2030, approximately 2.5 times the 2022 level. These figures illustrate how rapidly the industry as a whole is moving toward digitalization.
In this article, we provide a detailed look at the real estate industry's prospects for 2030, especially the feasibility of automated trading systems with AI agents, from the perspective of a leading industry player. We hope to provide readers with guidelines for understanding and appropriately responding to this wave of change.
The use of AI technology in the real estate industry has already been put to practical use in many fields. The following table summarizes representative examples.
| Fields of application | Specific services | Companies and cases | Effectiveness and accuracy |
|---|---|---|---|
| Price assessment | AI Automatic Appraisal System | Various players | |
| Loan Screening | Screening automation by AI | Flat 35 | Shorten screening time and improve accuracy |
| Property Search | AI recommendation function | Various real estate portal sites | Improvement of matching accuracy |
| Customer service | AI Chatbot | 24/7/365 service | Inquiry response efficiency |
| Market Analysis | Price Forecasting System | Rent forecasting | Improved accuracy of investment decisions |
However, challenges still exist in the implementation of AI technology, the most serious of which is the quality and quantity of data.
The most serious problem is the quality and quantity of data: a vast amount of high-quality data is essential for improving the accuracy of AI, but the real estate industry lacks standardization of information, and it takes a lot of effort to collect and organize the data.
Legal and regulatory development is another important issue. Real estate transactions are strictly regulated by law, and the use of AI technology requires careful consideration. In particular, there is a need to establish appropriate guidelines from the perspective of legal liability for AI-based appraisal results and the protection of personal information.
The need for human resource development should not be overlooked: in order to effectively utilize AI technology, it is essential to develop human resources who have a deep understanding of the technology in addition to conventional real estate knowledge. This is precisely where the "fusion of human imagination and technology," which I have always advocated, becomes important.
By 2030, a fully automated real estate transaction system with AI agents is expected to be realized. This system has the potential to fundamentally change the traditional real estate transaction process.
The envisioned flow of the automated transaction system is as follows
1. automatic collection and analysis of property information: AI agents collect all property information available on the market in real time and comprehensively analyze location conditions, building specifications, surrounding environment, etc.
2. precise matching of customer needs: AI automatically selects the optimal property based on a prospective buyer's past behavioral history, search patterns, budget, etc.
3. automated price negotiation: AI agents calculate a fair price based on market data and automatically negotiate the price among themselves
4. digitization of contract procedures: linked to blockchain technology, contracts are created, signed, and registered completely electronically.
AI agents in 2030 will achieve property matching with far greater accuracy than current recommender systems.
The sophistication of predictive analytics will enable them to read even latent needs not explicitly stated by the customer. For example, comprehensive analysis of potential job changes, changes in family structure, lifestyle transitions, etc., will enable us to propose optimal properties with an eye to the next 5 to 10 years.
Real-time market analysis will also dramatically improve the accuracy of property price fluctuation forecasts. It will be possible to analyze all factors, including economic indicators, demographics, infrastructure development plans, and the impact of climate change, in an integrated manner, and automatically select properties with high investment value.
Linkage with blockchain technology underpins the reliability of the automated trading system with AI agents.
Complete recording of transaction history ensures that property ownership transfers, price fluctuations, repair history, etc. are recorded in an unfalsifiable manner. This greatly improves transparency in real estate transactions and significantly reduces the risk of fraud and concealment.
Through the use of smart contracts, the terms of the contract are automatically executed. For example, a mechanism can be established to automatically execute payment and transfer of ownership the moment the conditions for delivery of the property are met.
In other countries, advanced examples of AI-based automated real estate transactions have already emerged.
Opendoor, a U.S. company that automates the buying and selling of homes through an online platform, has realized direct transactions without the need for traditional intermediaries, from AI-based price assessments to the conclusion of contracts. The company's system instantly quotes a purchase price simply by entering property information, and if conditions are met, the sale is completed within a few days.
Homelink in China has been innovating in the field of real estate technology since its founding in 2001, leading the Chinese market with its AI-based property matching system. The company works in partnership with China Construction Bank to provide integrated services from cash management to property transactions.
The size of the global real estate AI market is projected to reach $180.345 billion by 2030, with an impressive CAGR of 35% from 2023 to 2030.
The proliferation of automated buying and selling systems with AI agents will bring about a significant change in the role of the traditional real estate broker. However, this should not be viewed as a simple "replacement" but a more sophisticated "evolution.
The most important change is the enhancement of the consulting function: while AI will be responsible for routine tasks, human brokers will specialize in advanced consulting services that address the complex needs of their clients. For example, inheritance planning, tax optimization, asset portfolio construction, and other specialized consulting services that are difficult for AI to handle will become increasingly important.
Building human-like trust is another important value that cannot be replaced by AI. A real estate transaction is one of the most important decisions in one's life, and it often involves factors that cannot be measured by data alone, such as emotional aspects and family circumstances. A good brokerage can differentiate itself from AI by understanding these human factors and providing customer-focused service.
Working with technology, brokers' productivity will increase dramatically; they will be able to provide more efficient and higher quality service by utilizing the sophisticated market analysis and property information provided by AI.
Automated trading systems with AI agents offer many advantages to consumers.
The most direct benefit is a significant reduction in transaction costs. The traditional brokerage fee (3% of the property price plus 60,000 yen) is greatly reduced, allowing more people to access real estate transactions.
Increased transaction speed is another important benefit: transactions that used to take weeks or months can now be completed in days or weeks, thanks to automated processing by AI.
Increased transparency of information will allow consumers to make better decisions; the objective market analysis provided by AI will help avoid emotional misjudgments.
On the other hand, disadvantages also exist.
It is important to acquire basic real estate knowledge without blindly trusting AI's judgment.
Concerns about the handling of personal information cannot be ignored: AI systems require detailed personal information in order to perform highly accurate analysis, and proper management and protection of this information will be a challenge.
Advances in AI technology will create entirely new business models in the real estate industry.
Subscription-based housing services are expected to emerge. Services that allow users to use housing at a fixed monthly fee will become widespread, creating a new form of housing use that transcends the traditional concepts of "purchase" and "rental.
AI investment advisory services are another promising area. It is predicted that services will emerge in which AI proposes optimal real estate investment portfolios for individual investors and automatically executes purchases and sales.
Virtual real estate services will enable real estate experiences that transcend physical constraints, and when combined with VR technology, services that allow users to view properties around the world from the comfort of their own homes will become commonplace.
The table below outlines the new business models:
| Business Model | Service Description | Target Clients | Market Size Forecast |
|---|---|---|---|
| Subscription Housing | Monthly subscription housing use | Younger generations, transferees | Trillions of yen |
| AI Investment Advisory | Automated Investment Portfolio Management | Individual investors | Hundreds of billions of yen |
| Virtual Real Estate | VR/AR Utilization Services | All generations | Tens of billions of yen |
| Real estate data analysis | Market analysis and forecasting services | Companies and investors | Tens of billions of yen |
We will summarize what real estate industry participants should do now to prepare for the era of automated trading by AI agents in 2030.
Acquiring digital skills is a top priority: a wide range of technology knowledge is essential, from a basic understanding of AI technology to data analysis methods and digital marketing. We at INA&Associates also provide ongoing training for all employees to improve their digital literacy.
Redesigning the customer experience is also an important initiative, as it is necessary to clearly distinguish between the routine tasks that AI performs and the added value that humans should provide, and to design services that are more valuable to the customer.
Proactively collaborating with technology companies by building partnerships will help ensure competitive advantage. Instead of developing AI technology on their own, it is important to promote digital transformation efficiently through strategic alliances with specialized companies.
Consumers considering real estate transactions should also keep the following points in mind.
Acquiring basic real estate knowledge is important even in the age of AI; basic knowledge of how to identify a location, building structure, legal regulations, etc. is necessary to properly evaluate AI proposals.
It is important to objectively verify AI decisions by utilizing multiple sources of information. Instead of relying on the judgment of a single AI system, it is recommended to compare multiple services.
Keep a long-term perspective in mind: AI is excellent at analyzing short-term market trends, but it is important to consult with human experts when making decisions from a long-term perspective, such as life planning and family future.
After reading this article, we recommend the following actions
1. continue to gather information: regularly check the latest trends in real estate tech and PropTech to stay abreast of changes in the industry
2. improve your skills: start learning more about digital technologies and become competent in the age of AI
3. networking: develop relationships with experts in the technology field and companies that are taking forward-thinking initiatives
4. practical efforts: start improving your business using AI technology, even on a small scale
We at INA&Associates will walk with you through this era of change based on our philosophy of "fusing human imagination with technology." The era of automated trading by AI agents in 2030 is not far in the future. We hope that by starting preparations now, you will take advantage of this great transformation as an opportunity for growth.
The future of the real estate industry will be a more efficient and transparent market where technology and human wisdom are in harmony. Let's all actively participate in this transformation and work together to create an industry in which all stakeholders can benefit.
A: While a fully automated trading system is not expected to be realized until around 2030, partial automation has already begun. AI valuation and automated matching systems are currently in practical use, and the scope of automation is expected to expand in stages over the next five years. The timing of realization may vary depending on the status of legal development and resolution of technical issues.
A: They will not be completely eliminated; AI will take on routine tasks, while human brokers will specialize in advanced consulting services and building human relationships of trust. The importance of specialized consulting services that are difficult for AI to handle, such as inheritance planning, tax optimization, and dealing with complex family situations, is rather expected to increase.
A: Current AI valuation systems have achieved high accuracy in some cases, with an error rate of less than 5%. However, AI assessments are statistical forecasts based on past data, and are limited to individual property characteristics and rapid changes in the market; it is important to make a comprehensive judgment based on AI assessments as well as the opinions of experts.
A: Personal information protection is an important issue, as detailed personal information is required to achieve high accuracy in AI systems. Multi-layered security measures will be implemented, including encryption using blockchain technology, anonymization technology, and strict access control. In addition, revisions to the Personal Information Protection Law and industry guidelines are being developed.
A: With AI's sophisticated market analysis, information asymmetry will be reduced and more appropriate investment decisions can be made. However, real estate investment involves risks that are difficult to predict even with AI, such as market fluctuations, natural disasters, and changes in legal systems, etc. While AI can help improve the accuracy of investment decisions, it is important to understand that it does not completely eliminate risk.